A model establishing method and device for estimating relay life

Abstract

This application provides a model-building method and apparatus for estimating relay lifespan. The method includes: obtaining a single-condition Weibull life estimation model for estimating relay lifespan; obtaining a lifespan model parameter variation function; establishing a comprehensive-condition Weibull life estimation model for estimating relay lifespan based on the single-condition Weibull life estimation model and the lifespan model parameter variation function; discretizing the comprehensive-condition Weibull life estimation model to obtain a discretized model; and simplifying the discretized model to obtain an iterative relay lifespan estimation model. Therefore, implementing this method can effectively and accurately obtain the relay lifespan.

Description

Technical Field

[0001] This application relates to the field of electronic devices, and more specifically, to a method and apparatus for model building for estimating relay life. Background Technology

[0002] Currently, the methods commonly used in the industry to determine relay lifespan can be broadly categorized into the following two types:

[0003] The first method is to estimate the lifespan of a relay by statistically analyzing the number of times the relay is switched on and off, as well as the switching current and voltage.

[0004] The second method is to estimate the current lifespan of the relay by measuring the voltage drop across its terminals.

[0005] However, in practice, it has been found that the first approach typically calculates a value based on voltage and current, then subtracts that value from a preset value to obtain the remaining lifespan. However, this method does not delve into the relationship between relay lifespan consumption and voltage and current; it merely sets a coefficient based on experience, often resulting in significant estimation errors.

[0006] Meanwhile, the second method cannot ignore the fact that the relay has good conductivity, low contact resistance, and an overtravel design. This results in a very small contact resistance that remains relatively constant over a long period. Consequently, the method of estimating remaining lifespan by measuring the voltage across the relay is practically difficult to implement.

[0007] Therefore, it is clear that the current methods for obtaining relay lifespan cannot effectively and accurately determine the relay lifespan. Summary of the Invention

[0008] The purpose of this application is to provide a model building method and apparatus for estimating relay lifespan, which can effectively and accurately obtain the relay lifespan.

[0009] The first aspect of this application provides a model-building method for estimating relay lifespan, comprising:

[0010] Obtain a single-condition Weibull life estimation model for estimating relay life;

[0011] Obtain the parameter variation function of the lifetime model;

[0012] Based on the single-condition Weibull life estimation model and the life model parameter variation function, a comprehensive-condition Weibull life estimation model for estimating the relay life is established.

[0013] The Weibull life estimation model under the comprehensive operating conditions is discretized to obtain a discretized model;

[0014] The discretized model is simplified to obtain the relay life iterative estimation model.

[0015] In the above implementation process, this method can model the life loss process of relays using the Weibull distribution, and further create a Weibull life estimation model under comprehensive operating conditions by using the relationship between Weibull parameters and switching capacity. This avoids the problem that the Weibull distribution only applies to a single fault mode. Simultaneously, this method can also discretize the Weibull life estimation model under comprehensive operating conditions to obtain a discretized model that can be used in embedded software. After further simplification, it facilitates users to accurately determine the relay life by combining lookup tables.

[0016] Furthermore, the single-condition Weibull life estimation model is as follows:

[0017] ;

[0018] Where F(t) is the Weibull cumulative failure probability;

[0019] t represents the number of times the connection and disconnection are performed;

[0020] m is a shape parameter that matches the switching capacity;

[0021] η is a scale parameter that matches the on / off capacity.

[0022] Furthermore, the lifetime model parameters include shape parameters and scale parameters, wherein the step of obtaining the lifetime model parameter variation function includes:

[0023] Based on the correspondence between the switching capacity and the shape and scale parameters, a life model parameter variation function is established.

[0024] In the above implementation process, the method can determine the relay shape parameters and relay size parameters corresponding to the working voltage and working current in different switching capacities. Based on the correspondence between the working voltage, working current, relay shape parameters and relay size parameters, the method can establish a life model parameter variation function so that the relay life can be directly coupled with the working voltage and working current, thereby facilitating the determination of the current relay life based on the working voltage and working current.

[0025] Furthermore, the comprehensive operating condition Weibull life estimation model is as follows:

[0026] F (t|m, η) = Ψ (t, P (U, I));

[0027] Where F(t|m, η) is the Weibull cumulative failure probability;

[0028] t represents the number of times the circuit is switched on and off;

[0029] m is a shape parameter that matches the switching capacity;

[0030] η is a scale parameter that matches the on / off capacity;

[0031] P(U, I) is the parameter variation function of the lifetime model;

[0032] U is the operating voltage under the specified number of on / off cycles;

[0033] I represents the operating current under the specified number of switching cycles;

[0034] Where, (m, η) = P (U, I).

[0035] Furthermore, the step of discretizing the comprehensive operating condition Weibull life estimation model to obtain a discretized model includes:

[0036] Taking the derivative of the combined operating condition Weibull life estimation model, we get:

[0037] ;

[0038] Based on the i-th switching of the relay, dt=1 is determined, and the derivative formula is simplified to obtain:

[0039] △F=△Ψ(i,P(U,I))=f(i,P j );

[0040] By summing the simplified derivative formulas, we obtain the discretized model:

[0041] ;

[0042] Where F(t) is the Weibull cumulative failure probability;

[0043] t represents the number of times the circuit is switched on and off;

[0044] P(U, I) is the parameter variation function of the lifetime model;

[0045] U is the operating voltage under the specified number of on / off cycles;

[0046] I represents the operating current under the specified number of switching cycles;

[0047] i represents the current number of times the relay has been switched on and off;

[0048] j is the switching capacity label corresponding to both the operating voltage and the operating current of the relay.

[0049] In the above implementation process, the method discretizes the Weibull life estimation model under comprehensive operating conditions by taking derivatives and simplifying, thereby obtaining the life loss to represent each on-off condition. This allows the method to sum up the life loss under multiple on-off conditions when needed to obtain the relay life.

[0050] Furthermore, the relay lifetime iterative estimation model is as follows:

[0051] F k+1 =F k +K ij △F0;

[0052] Where i is the current number of times the relay is switched on and off;

[0053] j is the switching capacity label corresponding to both the operating voltage and the operating current of the relay;

[0054] K ij For P-based j and N i The lifespan baseline coefficient is obtained by looking up a table.

[0055] P j This represents the on / off capacity for the current operation.

[0056] N i This refers to the number of times the record was broken in history;

[0057] F0 is the initial Weibull cumulative failure probability;

[0058] F k This represents the current cumulative failure probability of Weibull.

[0059] F k+1 This represents the cumulative failure probability of the current Weibull run.

[0060] Furthermore, the method also includes:

[0061] Receive the cumulative failure rate used for calculation;

[0062] The cumulative failure rate is input into the relay life iterative estimation model for calculation to obtain the relay life.

[0063] In the above implementation process, the method can receive the cumulative failure rate input by the user, use the cumulative failure rate as the final estimate, use the relay life iterative estimation model to perform iterative calculation, thereby calculating the number of times the relay can be used, and then determine the number of times the relay can be used as the relay life and inform the user.

[0064] A second aspect of this application provides a model-building apparatus for estimating relay lifespan, the apparatus comprising:

[0065] The acquisition unit is used to acquire a single-condition Weibull life estimation model for estimating relay life.

[0066] The acquisition unit is also used to acquire the life model parameter change function;

[0067] A unit is established to establish a comprehensive operating condition Weibull life estimation model for estimating the life of the relay based on the single operating condition Weibull life estimation model and the life model parameter variation function.

[0068] Discrete units are used to discretize the comprehensive working condition Weibull life estimation model to obtain a discretized model;

[0069] A simplification unit is used to simplify the discretized model to obtain an iterative estimation model for relay life.

[0070] In the aforementioned implementation process, the device can model the lifespan loss process of relays using the Weibull distribution. Furthermore, by leveraging the relationship between Weibull parameters and switching capacity, it can create a Weibull lifespan estimation model under comprehensive operating conditions, thus avoiding the limitation of the Weibull distribution only addressing a single fault mode. Simultaneously, the device can discretize the Weibull lifespan estimation model under comprehensive operating conditions, obtaining a discretized model usable in embedded software. After further simplification, this model facilitates accurate determination of relay lifespan by users through table lookups.

[0071] A third aspect of this application provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor runs the computer program to cause the electronic device to perform the model building method for estimating relay life as described in any one of the first aspects of this application.

[0072] A fourth aspect of this application provides a computer-readable storage medium storing computer program instructions, which, when read and executed by a processor, perform the model-building method for estimating relay life as described in any one of the first aspects of this application. Attached Figure Description

[0073] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0074] Figure 1 A flowchart illustrating a model-building method for estimating relay lifespan, provided in an embodiment of this application;

[0075] Figure 2 This is a schematic diagram illustrating the interaction between the algorithm models provided in the embodiments of this application;

[0076] Figure 3 This is a schematic diagram of a model building device for estimating relay life, provided in an embodiment of this application. Detailed Implementation

[0077] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0078] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0079] Example 1

[0080] Please refer to Figure 1 , Figure 1 This embodiment provides a flowchart illustrating a model-building method for estimating relay lifespan. The model-building method for estimating relay lifespan includes:

[0081] S101. Obtain the single-condition Weibull life estimation model for estimating relay life.

[0082] In this embodiment, the single-condition Weibull life estimation model is as follows:

[0083] ;

[0084] Where F(t) is the Weibull cumulative failure probability;

[0085] t represents the number of times the connection and disconnection are performed;

[0086] m is a shape parameter that matches the switching capacity;

[0087] η is a scale parameter that matches the switching capacity.

[0088] In this embodiment, the single-condition Weibull lifetime estimation model is actually the Weibull cumulative failure probability function of the relay contact with respect to the number of times it is switched on and off, under the condition of a fixed voltage U and a fixed current I.

[0089] In this embodiment, the lifetime model parameters include shape parameters and scale parameters.

[0090] In this embodiment, the parameters (m, η) are related to the characteristics and operating state of the relay contacts. For the same relay, under a certain operating state (fixed voltage u, fixed current i), i.e., a certain switching capacity, the values ​​of these parameters can be considered fixed. This is also a characteristic of the Weibull distribution, which can only describe the fault distribution under a single operating condition.

[0091] In this embodiment, the parameters (m, η) are generally fitted using experimental data. That is, a set of relays is selected, and disconnection experiments are performed under the conditions of voltage U0 and current I0. The number of times each relay ultimately fails (t1, t2, ..., t) is recorded in sequence. n By calculating the median rank, the fault data is processed into a cumulative failure rate, and then fitted using the least squares method to finally determine a set of (m, η).

[0092] In this embodiment, the median rank can be calculated using the following formula:

[0093] ;

[0094] i indicates which data point is being read;

[0095] n represents the total number of data;

[0096] The parameters can be fitted using the least squares method or maximum likelihood estimation; the derivation process for the fitting will not be elaborated here.

[0097] In this embodiment, according to reliability theory, the operating time corresponding to a given reliability is called the reliable lifetime. For example, if the given reliability is R=0.95, the corresponding operating time is denoted as t(0.95), which is the reliable lifetime. When the reliability is unknown, as long as the operating time exceeds t(0.95), the product's reliability will be lower than the given value of 95%, and more products may fail.

[0098] In this embodiment, the method uses the cumulative failure rate of the product, F=1-R, which corresponds to reliability. In the example above, F=0.05, meaning that statistically, 5% of the products will fail. An increase in the cumulative failure rate of the product indicates that the product's reliability lifespan is being consumed. Therefore, this method uses the cumulative failure rate to represent the product's depletion lifespan.

[0099] S102. Based on the correspondence between switching capacity and shape and scale parameters, establish the parameter variation function of the lifetime model.

[0100] In this embodiment, based on the characteristics of the relay, it is known that the larger the interrupting voltage and current, i.e., the larger its switching capacity, the faster the wear. Therefore, its corresponding lifetime model parameters (m, η) are also different. For a relay, its Weibull cumulative failure probability function is a family of functions, denoted as:

[0101] ;

[0102] Since different switching capacities correspond to different (m, η) parameters, we can assume that a functional relationship exists, denoted as:

[0103] (m, η) = P(U, I);

[0104] As can be seen, this formula is actually a set of functions, which assumes that for each on / off capacity, there is a one-to-one correspondence between it and a set of (m, η).

[0105] S103. Based on the single-condition Weibull life estimation model and the life model parameter variation function, establish a comprehensive-condition Weibull life estimation model for estimating relay life.

[0106] In this embodiment, the comprehensive operating condition Weibull life estimation model is as follows:

[0107] F (t|m, η) = Ψ (t, P (U, I));

[0108] F(t|m, η) is the Weibull cumulative failure probability;

[0109] t represents the number of times the connection and disconnection are performed;

[0110] m is a shape parameter that matches the switching capacity;

[0111] η is a scale parameter that matches the on / off capacity;

[0112] P(U, I) is the parameter variation function of the lifetime model;

[0113] U is the operating voltage under a certain number of switching cycles;

[0114] I represents the operating current under the number of on / off cycles;

[0115] Where, (m, η) = P (U, I).

[0116] In this embodiment, the functional relationship between (m, η) and the on / off capacity is determined generally by fitting experimentally tested parameters. That is, using the test data from the above steps, (m) can be obtained. i η i ) Corresponding to P i Using either the least squares method or maximum likelihood estimation, fit m respectively. i η i Corresponding to p i The functional relationship.

[0117] In this embodiment, based on experience, m i Related to the consistency of the relay, it can take a value between 3 and 5; η i Approximate to P i The average number of times the circuit is switched on and off, and P i It exhibits an exponential relationship.

[0118] S104. Discretize the Weibull life estimation model under comprehensive operating conditions to obtain a discretized model.

[0119] As an optional implementation, the steps for discretizing the comprehensive operating condition Weibull life estimation model to obtain the discretized model include:

[0120] Taking the derivative of the combined operating condition Weibull life estimation model, we get:

[0121] ;

[0122] Based on the i-th switching of the relay, we determine dt=1 and simplify the derivative formula to obtain:

[0123] △F=△Ψ(i,P(U,I))=f(i,P j );

[0124] By summing the simplified derivative formulas, we obtain the discretized model:

[0125] ;

[0126] Where F(t) is the Weibull cumulative failure probability;

[0127] t represents the number of times the connection and disconnection are performed;

[0128] P(U, I) is the parameter variation function of the lifetime model;

[0129] U is the operating voltage under a certain number of switching cycles;

[0130] I represents the operating current under the number of on / off cycles;

[0131] i represents the current number of times the relay has been switched on and off;

[0132] j represents the switching capacity label corresponding to the relay's operating voltage and operating current.

[0133] In this embodiment, n is the assumed number of times the relay will fail after being switched on and off n times.

[0134] S105. The discretized model is simplified to obtain the relay life iterative estimation model.

[0135] In this embodiment, the relay lifetime iterative estimation model is as follows:

[0136] F k+1 =F k +K ij △F0;

[0137] i represents the current number of times the relay has been switched on and off;

[0138] j represents the switching capacity label corresponding to the relay's operating voltage and operating current.

[0139] K ij For P-based j and N i The lifespan baseline coefficient is obtained by looking up a table.

[0140] P j This represents the on / off capacity for the current operation.

[0141] N i This refers to the number of times the record was broken in history;

[0142] F0 is the initial Weibull cumulative failure probability;

[0143] F k This represents the current cumulative failure probability of Weibull.

[0144] F k+1 This represents the cumulative failure probability of the current Weibull run.

[0145] In this embodiment, for the convenience of counting, the lifespan consumed under the standard operating conditions (F0, P0) is set as the benchmark, and the lifespan consumed under different switching capacities can be converted.

[0146] Assuming a certain capacity W0 is used as a baseline, then the lifetime factor is:

[0147] ;

[0148] That is, assuming the relay lifespan consumed is 1 when the switching capacity is W0, then when the switching capacity is P iThe relay life consumed is k i Then there is a corresponding lifetime coefficient array (k1, k2, ... k n ).

[0149] Meanwhile, the lifespan coefficient of a relay each time depends not only on the switching capacity but also on the number of switching operations the relay has accumulated. That is, for the same switching capacity P0, the currently accumulated equivalent number of switching operations is N. j At that time, there were:

[0150] ;

[0151] In summary, the actual lifespan factor can be expressed as:

[0152] ;

[0153] Then according to k i From the definition, we can obtain the life coefficient table of the switching capacity P of the relay after a certain number of switching cycles N.

[0154] In this embodiment, it is assumed that the relay has been switched on and off by N. i Next, the current on / off capacity is P. j The coefficient for the current on / off state can be obtained as K by looking up the table. ij The overall lifespan consumed can then be expressed using the following iterative formula:

[0155] △F0 = f(0, P0);

[0156] F1=F0+K 11 △F0;

[0157] F k+1 =F k +K ij △F0;

[0158] Where F1∈(N1, N2, ..., N) m ), i, j, k∈ (1,2,3,…);

[0159] k ij According to F i P j The result was obtained from the lifespan coefficient table.

[0160] The above-mentioned lifespan factor table is shown in Table 1 below:

[0161] Table 1

[0162]

[0163] Please see Figure 2 , Figure 2The diagram illustrates the interaction between the algorithm models. Specifically, the single-state Weibull lifetime model corresponds to the single-condition Weibull lifetime estimation model; the relationship between model parameters and initial capacity corresponds to the lifetime model parameter variation function; the relay contact lifetime model under combined operating conditions corresponds to the combined operating condition Weibull lifetime estimation model; the discretized lifetime model corresponds to the discretized model; and the simplification of the model and its application in the program correspond to the relay lifetime iterative estimation model and its application.

[0164] S106, Receive the cumulative failure rate used for calculation.

[0165] S107. Input the cumulative failure rate into the relay life iterative estimation model for calculation to obtain the relay life.

[0166] In this embodiment, according to the national standard GB-6583, reliability refers to the ability of a product to perform its intended function under specified conditions and within a specified time. Product reliability can be evaluated through reliability, failure rate, and mean time between failures (MTBF). Therefore, in engineering, this "specified time" is usually used to describe the design life of a product, also known as its reliability life. For products like relays, the time life is usually converted into the number of operations under certain conditions. For example, a relay, operating at an ambient temperature of 40°C, interrupts a DC voltage of 500V and a current of 10A 50,000 times over 15 years with a cumulative failure rate of ≤10%. For this relay, the 50,000 interruptions represent its design life, corresponding to a cumulative failure rate of 10%. As can be seen from the cumulative failure rate curve in the Weibull distribution below, the cumulative failure rate increases continuously with the increase in the number of operations.

[0167] Therefore, for the same product, its working life will differ depending on the acceptable cumulative failure rate. The acceptable cumulative failure rate depends on the balance between maintenance costs and the services provided, which falls under the category of business decisions.

[0168] For designers, if decision-makers have determined their acceptable cumulative failure rate p, the available equivalent number of relays can be calculated using the following formula:

[0169] ;

[0170] For ease of calculation, the (m, η) above are the fitting parameters under standard working conditions, and N above is the equivalent number based on N0.

[0171] In this embodiment, the subject executing the method can be a computing device such as a computer or server, and no limitation is made in this embodiment.

[0172] In this embodiment, the subject executing the method can also be a smart device such as a smartphone or tablet, and no limitation is made in this embodiment.

[0173] As can be seen, the model building method for estimating relay life described in this embodiment, based on the characteristics of relay aging, adopts an aging model based on Weibull theory and proposes a functional relationship between model parameters and relay operating state. Compared with a simple linear model, it is closer to the actual operating state of the relay, thereby improving the accuracy of power battery relay life estimation. At the same time, in order to realize its application in embedded systems, this method further discretizes the relatively complex algorithm model, proposes a simplified model, and uses a lookup table algorithm to significantly reduce the amount of computation, making its application in embedded systems possible.

[0174] Example 2

[0175] Please refer to Figure 3 , Figure 3 This is a schematic diagram of a model-building device for estimating relay lifespan, provided in this embodiment. Figure 3 As shown, the model-building device for estimating relay life includes:

[0176] The acquisition unit 210 is used to acquire a single-condition Weibull life estimation model for estimating relay life.

[0177] The acquisition unit 210 is also used to acquire the life model parameter change function;

[0178] Unit 220 is established to build a comprehensive Weibull life estimation model for estimating relay life based on a single-condition Weibull life estimation model and a life model parameter variation function.

[0179] Discrete element 230 is used to discretize the comprehensive working condition Weibull life estimation model to obtain a discretized model;

[0180] The simplification unit 240 is used to simplify the discretized model to obtain the relay life iterative estimation model.

[0181] As an optional implementation, the single-condition Weibull life estimation model is as follows:

[0182] ;

[0183] F(t) is the Weibull cumulative failure probability;

[0184] t represents the number of times the connection and disconnection are performed;

[0185] m is a shape parameter that matches the switching capacity;

[0186] η is a scale parameter that matches the switching capacity.

[0187] As an optional implementation, the lifetime model parameters include shape parameters and scale parameters. Specifically, the acquisition unit is used to establish a lifetime model parameter variation function based on the correspondence between the switching capacity and the shape and scale parameters.

[0188] As an optional implementation method, the combined operating condition Weibull life estimation model is as follows:

[0189] F (t|m, η) = Ψ (t, P (U, I));

[0190] F(t|m, η) is the Weibull cumulative failure probability;

[0191] t represents the number of times the circuit is switched on and off;

[0192] m is a shape parameter that matches the switching capacity;

[0193] η is a scale parameter that matches the on / off capacity;

[0194] P(U, I) is the parameter variation function of the lifetime model;

[0195] U is the operating voltage under a certain number of switching cycles;

[0196] I represents the operating current under the number of on / off cycles;

[0197] Where, (m, η) = P (U, I).

[0198] As an optional implementation, the discrete element is specifically used to differentiate the combined operating condition Weibull life estimation model, resulting in:

[0199] ;

[0200] Based on the i-th switching of the relay, we determine dt=1 and simplify the derivative formula to obtain:

[0201] △F=△Ψ(i,P(U,I))=f(i,P j );

[0202] By summing the simplified derivative formulas, we obtain the discretized model:

[0203] ;

[0204] Where F(t) is the Weibull cumulative failure probability;

[0205] t represents the number of times the circuit is switched on and off;

[0206] P(U, I) is the parameter variation function of the lifetime model;

[0207] U is the operating voltage under a certain number of switching cycles;

[0208] I represents the operating current under the number of on / off cycles;

[0209] i represents the current number of times the relay has been switched on and off;

[0210] j represents the switching capacity label corresponding to the relay's operating voltage and operating current.

[0211] As an optional implementation, the relay lifetime iterative estimation model is as follows:

[0212] F k+1 =F k +K ij △F0;

[0213] i represents the current number of times the relay has been switched on and off;

[0214] j represents the switching capacity label corresponding to the relay's operating voltage and operating current.

[0215] K ij For P-based j and N i The lifespan baseline coefficient is obtained by looking up a table.

[0216] P j This represents the on / off capacity for the current operation.

[0217] N i This refers to the number of times the record was broken in history;

[0218] F0 is the initial Weibull cumulative failure probability;

[0219] F k This represents the current cumulative failure probability of Weibull.

[0220] F k+1 This represents the cumulative failure probability of the current Weibull run.

[0221] As an optional implementation, the model-building apparatus for estimating relay life further includes:

[0222] The receiving unit 250 is used to receive the cumulative failure rate for calculation;

[0223] The calculation unit 260 is used to input the cumulative failure rate into the relay life iterative estimation model for calculation to obtain the relay life.

[0224] In this embodiment, the explanation of the model building device for estimating relay life can be referred to the description in Embodiment 1, and will not be repeated here.

[0225] As can be seen, the model building device for estimating relay life described in this embodiment can model the relay's lifespan loss process using the Weibull distribution. Furthermore, by leveraging the relationship between Weibull parameters and switching capacity, it can create a Weibull lifespan estimation model under comprehensive operating conditions, thus avoiding the limitation of the Weibull distribution only addressing a single fault mode. Simultaneously, the device can discretize the Weibull lifespan estimation model under comprehensive operating conditions, obtaining a discretized model usable in embedded software. After further simplification, this model facilitates accurate relay lifespan determination by users through table lookup.

[0226] This application provides an electronic device, including a memory and a processor. The memory stores a computer program, and the processor runs the computer program to enable the electronic device to perform the model building method for estimating relay life in embodiment 1 of this application.

[0227] This application provides a computer-readable storage medium storing computer program instructions. When these computer program instructions are read and executed by a processor, they perform the model-building method for estimating relay lifespan described in Embodiment 1 of this application.

[0228] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0229] In addition, the functional modules in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0230] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0231] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application. It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0232] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0233] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

Claims

1. A model building method for estimating relay life, characterized by, The method comprises: obtaining a single working condition Weibull life estimation model for estimating the life of the relay; wherein the single working condition Weibull life estimation model is: ； wherein F(t) is a Weibull cumulative failure probability; t is the number of times of switching; m is a shape parameter matched with the switching capacity; η is a scale parameter matched with the switching capacity; obtaining a life model parameter change function; wherein the life model parameters comprise the shape parameter and the scale parameter, and wherein the step of obtaining the life model parameter change function comprises: establishing a life model parameter change function according to a corresponding relationship between the switching capacity and both the shape parameter and the scale parameter; the switching capacity comprises a working voltage and a working current; wherein, due to different switching capacities, the corresponding (m, η) parameters are different, denoted as (m, η) = P(U, I); m is a shape parameter matched with the switching capacity; η is a scale parameter matched with the switching capacity; P(U, I) is a life model parameter change function; (m, η) = P(U, I) is actually a function group, and it is considered that there is a one-to-one corresponding relationship between a group of (m, η) and each switching capacity; based on the single working condition Weibull life estimation model and the life model parameter change function, establishing a comprehensive working condition Weibull life estimation model for estimating the life of the relay; wherein the comprehensive working condition Weibull life estimation model is: F[t| (m, η)] = Ψ(t, P(U, I)); wherein F[t| (m, η)] is a Weibull cumulative failure probability; t is the number of times of switching; m is a shape parameter matched with the switching capacity; η is a scale parameter matched with the switching capacity; P(U, I) is a life model parameter change function; U is the working voltage under the number of times of switching; I is the working current under the number of times of switching; discretizing the comprehensive working condition Weibull life estimation model to obtain a discretized model; simplifying the discretized model to obtain a relay life iterative estimation model; wherein the relay life iterative estimation model is: ； wherein i is the current number of times of switching of the relay; j is a switching capacity tag corresponding to both the working voltage and the working current of the relay; K ij is a life reference coefficient obtained by looking up a table based on P j and N i ; P j for the on-off capacity of the current time; N i the equivalent number of make-and-breaks that the relay has consumed; Fk = current Weibull cumulative failure probability for the kth iteration calculation; Weibull cumulative failure probability calculated for the kth iteration.

2. The method of claim 1, wherein, The method further comprises: receiving a cumulative failure rate for calculation; inputting the cumulative failure rate into the relay life iterative estimation model for calculation to obtain the life of the relay.

3. A model-building device for estimating relay lifespan, characterized in that, The model establishment device for estimating the life of the relay comprises: an obtaining unit, configured to obtain a single working condition Weibull life estimation model for estimating the life of the relay; wherein the single working condition Weibull life estimation model is: ； wherein F(t) is a Weibull cumulative failure probability; t is the number of times of switching; m is a shape parameter matched with the switching capacity; η is a scale parameter matched with the switching capacity; The acquisition unit is further configured to acquire a life model parameter change function; wherein the life model parameters comprise a shape parameter and a scale parameter, and the acquisition unit is specifically configured to establish the life model parameter change function according to a corresponding relationship between the on-off capacity and the shape parameter and the scale parameter; the on-off capacity comprises a working voltage and a working current; wherein, due to different on-off capacities, the corresponding (m, η) parameters are different, and are denoted as (m, η) = P(U, I); (m, η) = P(U, I) is actually a function group, and it is considered that there is a one-to-one corresponding relationship between a group of (m, η) and each on-off capacity; wherein m is a shape parameter matched with the on-off capacity; η is a scale parameter matched with the on-off capacity; and P(U, I) is the life model parameter change function; The establishment unit is configured to establish a comprehensive working condition Weibull life estimation model for estimating the relay life based on the single working condition Weibull life estimation model and the life model parameter change function; wherein the comprehensive working condition Weibull life estimation model is: F[t| (m, η)] = Ψ(t, P(U, I)); wherein F[t| (m, η)] is a Weibull cumulative failure probability; t is the on-off frequency; m is a shape parameter matched with the on-off capacity; η is a scale parameter matched with the on-off capacity; P(U, I) is the life model parameter change function; U is the working voltage under the on-off frequency; and I is the working current under the on-off frequency; The discretization unit is configured to perform discretization processing on the comprehensive working condition Weibull life estimation model to obtain a discretization model; The simplification unit is configured to perform simplification processing on the discretization model to obtain a relay life iterative estimation model; wherein the relay life iterative estimation model is: wherein i is the current on-off frequency of the relay; and j is an on-off capacity tag corresponding to the working voltage and the working current of the relay. The electronic device comprises a memory and a processor, the memory is configured to store a computer program, and the processor is configured to run the computer program to enable the electronic device to execute the model establishment method for estimating the relay life according to any one of claims 1 to 2. The readable storage medium stores computer program instructions, and the computer program instructions are read and run by a processor to execute the model establishment method for estimating the relay life according to any one of claims 1 to 2. ​ ​ ​ ； ​ ​ K ij is a life reference coefficient obtained by looking up a table based on P j and N i ; P j for the on-off capacity of the current time; N i the equivalent on-off number of times the relay has consumed; Fk = current Weibull cumulative failure probability for the kth iteration calculation; Weibull cumulative failure probability calculated for the kth iteration.

4. An electronic device, comprising: ​ 5. A readable storage medium characterized by, ​

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